Assistant Professor | School of Information Science
Only 6 weeks left! 1 group has been approved by IRB
You can learn a lot about a quantitative study using just these!
General Design Classifications for Selection of Difference Statistical Methods
It’s all about the levels of the IV
Designs are usually described in terms of:
The researcher will typically state the design:
EX: A single factor design with 3 levels
EX: A 2 x 2 design with repeated measures
EX: A 3 x 3 x 2 factorial design
Note: Factor is another name for IV
Single factor designs only have one IV
EX: The effect of time of class (morning, afternoon, night) on student engagement.
EX: Students’ perceptions of instructor effectiveness over time.
Ikeola and Marian are examining campaigns using visual images can influence HPV vaccine behavioral intentions and eventual uptake of the HPV vaccine.
Includes more than one IV
EX: The effect of time of class (morning, afternoon, night) and student sex (male, female) on student engagement.
This is called a 3 x 2 factorial design.
The numbers represent the number of levels (3 levels of time of class and 2 levels of sex).
The number of numbers represents the number of IVs (time of class and sex)
If you have a 4 x 2 x 3 factorial design…
How many IVs do you have?
What are the levels of each IV?
How many groups would you need for the study?
Elizabeth, Madelyn, and Ansley are examining how message sender status on Instagram influences behavioral intention / adoption.
This is currently a single-subject design. How would you make it a between-subjects design?
Two or more IVs
Participants experience all conditions
EX: The effect of teaching style (traditional or inquiry based) on student engagement over time (pretest and posttest)
To assess the CIS courses in the School of Information Science, we collect data from all course sections in August, December, January, and April to see if participation in course influences public speaking self-efficacy.
EX: The effect of class time on public speaking self-efficacy over time.
“Such a design might have two between-groups independent variables with three and four levels, respectively, and have one within-subjects independent variable with two levels.
It would be described as a 3 × 4 × 2 factorial design with repeated measures on the third factor.”
Basically, if it has a BG component and a WS component, it is a mixed design!
If you recognize the design, you can generally determine the type of test needed.
The design classification ultimately drives the appropriate statistics.
Three major statistical assumptions:
Data Analysis and Interpretation: Basic Difference Questions
We are going to go through A LOT of tests.
I’m not going to show you how to run each one (i.e., what buttons to press)
IMO - it is more important to know which test is appropriate and how to interpret it. Once you figure out which test to run, there is a tutorial out there somewhere.
A Chi-Square Test of Independence is used to determine whether or not there is a significant association between two categorical variables.
How does the proportion of smokers who are female and male in our sample differ from the proportion of smokers in the population who are female and male?